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| Criterion |  Growth Funnel Analysis |  Product Strategy Counter Metrics |  UX Research HEART Framework |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | When a headline metric could mask side effects, it adds guardrail signals against unwanted outcomes. It connects customer value, product logic, and decision priorities. The result is captured as a counter-metric list and guardrail definitions. | Helps clarify observations, needs, and patterns in concrete terms. It groups observations into patterns, questions, and decisions. The result is captured as a HEART-GSM table and dashboard. | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. |
Complexitydifferent | Medium | Low | Medium | High |
Timedifferent | 1-3 h | 30-60 min | 120 min initial, dann laufend | 1-4 Wochen |
Participantsdifferent | 1-5 | 2-6 | 3-6 | 1-6 |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Counter Metric List, Guardrail Definitions | HEART-GSM Table, Dashboard | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | MetricsMeasurementStrategyExperiments | MetricsUX researchMeasurementSatisfaction | ExperimentsGrowthAnalyticsValidation |